Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2016-04-18 12:13:45	ga_s2am_ard_3-2-1_49KGR_2016-04-18_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JNM_2016-08-30_final.stac-item
2017-02-02 12:13:15	ga_s2am_ard_3-2-1_49JGN_2017-02-02_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_50KMC_2017-02-19_final.stac-item
2017-03-18 11:51:11	ga_s2am_ard_3-2-1_50KQC_2017-03-18_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50KMC_2018-01-12_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50JPM_2018-01-19_final.stac-item
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_49JGM_2018-01-28_final.stac-item
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50JLL_2018-02-01_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_50KKA_2018-03-06_final.stac-item
2018-06-04 12:02:50	ga_s2am_ard_3-2-1_50KLB_2018-06-04_final.stac-item
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_50KKB_2018-06-04_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_49JGN_2018-06-14_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50JKS_2018-07-04_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JQP_2018-09-26_final.stac-item
2018-10-03 11:32:47	ga_s2am_ard_3-2-1_50HPJ_2018-10-03_final.stac-item
2018-10-06 11:46:03	ga_s2am_ard_3-2-1_50JPL_2018-10-06_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JKN_2018-10-22_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HLH_2018-10-29_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HNK_2018-10-29_final.stac-item
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50JNM_2018-11-05_final.stac-item
2018-12-11 12:05:21	ga_s2am_ard_3-2-1_49JGK_2018-12-11_final.stac-item
2019-01-20 12:04:28	ga_s2am_ard_3-2-1_49KGP_2019-01-20_final.stac-item
2019-02-23 11:46:11	ga_s2am_ard_3-2-1_50JQL_2019-02-23_final.stac-item
2019-03-31 12:03:38	ga_s2am_ard_3-2-1_50KMB_2019-03-31_final.stac-item
2019-04-20 12:03:26	ga_s2am_ard_3-2-1_50KMC_2019-04-20_final.stac-item
2019-05-07 11:56:18	ga_s2am_ard_3-2-1_50JKM_2019-05-07_final.stac-item
2019-05-10 12:04:35	ga_s2am_ard_3-2-1_49KGP_2019-05-10_final.stac-item
2019-05-10 12:04:39	ga_s2am_ard_3-2-1_50JMT_2019-05-10_final.stac-item
2019-06-26 11:53:35	ga_s2am_ard_3-2-1_50KMC_2019-06-26_final.stac-item
2019-08-08 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-08-08_final.stac-item
2019-08-15 11:56:21	ga_s2am_ard_3-2-1_50JNL_2019-08-15_final.stac-item
2019-08-18 12:03:47	ga_s2am_ard_3-2-1_50KKB_2019-08-18_final.stac-item
2019-08-18 12:05:00	ga_s2am_ard_3-2-1_50JKS_2019-08-18_final.stac-item
2019-09-14 11:56:35	ga_s2am_ard_3-2-1_50HMK_2019-09-14_final.stac-item
2019-09-18 11:37:06	ga_s2am_ard_3-2-1_50HPH_2019-09-18_final.stac-item
2019-10-01 11:46:31	ga_s2am_ard_3-2-1_50HQK_2019-10-01_final.stac-item
2019-10-21 11:43:22	ga_s2am_ard_3-2-1_50KRC_2019-10-21_final.stac-item
2019-11-16 12:04:33	ga_s2am_ard_3-2-1_49KGP_2019-11-16_final.stac-item
2020-01-09 11:42:58	ga_s2am_ard_3-2-1_50KRD_2020-01-09_final.stac-item
2020-01-15 12:04:25	ga_s2am_ard_3-2-1_49KGP_2020-01-15_final.stac-item
2020-02-11 11:53:46	ga_s2am_ard_3-2-1_50KNA_2020-02-11_final.stac-item
2020-02-18 11:43:45	ga_s2am_ard_3-2-1_50KQA_2020-02-18_final.stac-item
2020-03-25 12:04:01	ga_s2am_ard_3-2-1_50KKA_2020-03-25_final.stac-item
2020-04-24 12:03:46	ga_s2am_ard_3-2-1_50KKB_2020-04-24_final.stac-item
2020-04-28 11:43:21	ga_s2am_ard_3-2-1_50KRC_2020-04-28_final.stac-item
2020-05-14 12:04:09	ga_s2am_ard_3-2-1_49KHR_2020-05-14_final.stac-item
2020-06-14 11:36:58	ga_s2am_ard_3-2-1_50HPJ_2020-06-14_final.stac-item
2020-06-23 12:04:48	ga_s2am_ard_3-2-1_49JHN_2020-06-23_final.stac-item
2020-06-30 11:53:16	ga_s2am_ard_3-2-1_50KRC_2020-06-30_final.stac-item
2020-07-07 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2020-07-07_final.stac-item
2020-08-16 11:47:16	ga_s2am_ard_3-2-1_50HMH_2020-08-16_final.stac-item
2020-09-08 11:56:22	ga_s2am_ard_3-2-1_50JNL_2020-09-08_final.stac-item
2020-10-01 12:05:20	ga_s2am_ard_3-2-1_49JGL_2020-10-01_final.stac-item
2020-12-17 11:56:28	ga_s2am_ard_3-2-1_50HNK_2020-12-17_final.stac-item
2020-12-30 12:03:56	ga_s2am_ard_3-2-1_50KLA_2020-12-30_final.stac-item
2021-01-03 11:44:16	ga_s2am_ard_3-2-1_50KRU_2021-01-03_final.stac-item
2021-02-05 11:54:54	ga_s2am_ard_3-2-1_50JMS_2021-02-05_final.stac-item
2021-03-04 11:46:08	ga_s2am_ard_3-2-1_50JNM_2021-03-04_final.stac-item
2021-05-19 12:06:04	ga_s2am_ard_3-2-1_50JLM_2021-05-19_final.stac-item
2021-05-23 11:44:17	ga_s2am_ard_3-2-1_50KRU_2021-05-23_final.stac-item
2021-07-19 11:36:23	ga_s2am_ard_3-2-1_50JQL_2021-07-19_final.stac-item
2021-08-31 11:46:10	ga_s2am_ard_3-2-1_50JNM_2021-08-31_final.stac-item
2021-09-03 11:56:26	ga_s2am_ard_3-2-1_50JLL_2021-09-03_final.stac-item
2021-09-30 11:43:23	ga_s2am_ard_3-2-1_50KRC_2021-09-30_final.stac-item
2021-10-07 11:37:26	ga_s2am_ard_3-2-1_50HPG_2021-10-07_final
2021-10-13 11:53:26	ga_s2am_ard_3-2-1_50KPC_2021-10-13_final.stac-item
2021-10-16 12:03:43	ga_s2am_ard_3-2-1_50KMB_2021-10-16_final.stac-item
2021-11-08 12:14:44	ga_s2am_ard_3-2-1_49JGN_2021-11-08_final.stac-item
2022-01-24 12:03:23	ga_s2am_ard_3-2-1_50KMC_2022-01-24_final.stac-item
2022-02-26 12:14:30	ga_s2am_ard_3-2-1_49KGP_2022-02-26_final.stac-item
2022-03-28 12:14:59	ga_s2am_ard_3-2-1_49JGM_2022-03-28_final.stac-item
2022-04-21 11:52:24	ga_s2am_ard_3-2-1_50KQG_2022-04-21_final
2022-05-14 12:04:03	ga_s2am_ard_3-2-1_49KHR_2022-05-14_final.stac-item
2022-06-07 11:46:27	ga_s2am_ard_3-2-1_50JPL_2022-06-07_final.stac-item
2022-06-23 12:04:11	ga_s2am_ard_3-2-1_49KHR_2022-06-23_final.stac-item
2022-08-19 11:56:06	ga_s2am_ard_3-2-1_50JMN_2022-08-19_final.stac-item
2022-08-29 11:56:23	ga_s2am_ard_3-2-1_50JLM_2022-08-29_final.stac-item
2022-09-18 11:54:46	ga_s2am_ard_3-2-1_50JNT_2022-09-18_final.stac-item
2022-09-25 11:46:33	ga_s2am_ard_3-2-1_50JML_2022-09-25_final.stac-item
2022-11-24 11:45:03	ga_s2am_ard_3-2-1_50JQR_2022-11-24_final.stac-item
2022-12-30 12:05:40	ga_s2am_ard_3-2-1_50JKP_2022-12-30_final.stac-item
2023-01-06 11:53:30	ga_s2am_ard_3-2-1_50KMC_2023-01-06_final.stac-item
2023-01-16 11:53:17	ga_s2am_ard_3-2-1_50KPC_2023-01-16_final.stac-item
2023-02-22 11:43:59	ga_s2am_ard_3-2-1_50KRV_2023-02-22_nrt.stac-item
2023-05-26 11:53:24	ga_s2am_ard_3-2-1_50KPC_2023-05-26_final
2023-06-02 11:46:38	ga_s2am_ard_3-2-1_50HPK_2023-06-02_final
2023-06-05 11:53:25	ga_s2am_ard_3-2-1_50KPC_2023-06-05_final
2023-06-21 12:13:58	ga_s2am_ard_3-2-1_50KKA_2023-06-21_final
2023-08-18 11:36:54	ga_s2am_ard_3-2-1_50HQJ_2023-08-18_final
2023-08-27 12:06:01	ga_s2am_ard_3-2-1_50JKN_2023-08-27_final
2023-09-03 11:56:16	ga_s2am_ard_3-2-1_50JLM_2023-09-03_final
2023-10-23 11:54:19	ga_s2am_ard_3-2-1_50KPU_2023-10-23_final
2023-12-12 11:53:26	ga_s2am_ard_3-2-1_50KMC_2023-12-12_final
2023-12-12 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2023-12-12_final
2023-12-28 12:13:52	ga_s2am_ard_3-2-1_49KHR_2023-12-28_final
2024-01-07 12:14:52	ga_s2am_ard_3-2-1_49JGM_2024-01-07_final
2024-02-03 12:03:37	ga_s2am_ard_3-2-1_50KLB_2024-02-03_final
2024-02-10 11:53:17	ga_s2am_ard_3-2-1_50KPC_2024-02-10_final
2024-03-14 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2024-03-14_final

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years